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Estimating Option Implied Probability Distributions for Inflation

Schuttenbeld, Maarten (author)

This thesis investigates the estimation of option-implied probability density functions for inflation using inflation options, focusing not only on the expected value but the whole distribution. The aim is to identify the most effective method for measuring the market expectation of future inflation. The research explores both parametric and non...

master thesis 2023

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A novel cosine network for pricing European and barrier options under stochastic volatility models

Bangerter, Felix (author)

This thesis presents a comprehensive exploration of the rough Heston model as a means to enhance financial derivative pricing and calibration in the context of the complex behavior of market volatility. Recognizing the limitations of classical models, such as the Black-Scholes and the standard Heston model, which assume constant or mean...

master thesis 2023

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Solving multivariate expectations using dimension-reduced fourier-cosine series expansion and its application in finance

Brands, Marnix (author)

The computation of multivariate expectations is a common task in various fields related to probability theory. This thesis aims to develop a generic and efficient solver for multivariate expectation problems, with a focus on its application in the field of quantitative finance, specifically for the quantification of Counterparty Credit Risk (CCR...

master thesis 2023

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Pricing multi-dimensional American options using kernel ridge regression

Chen, Qianqian (author)

American option pricing has been an active research area in financial engineering over the past few decades. Since no analytic closed-form solution exists, various numerical approaches have been developed. Among all proposed methods, the least square Monte Carlo(LSMC) approach is the most successful and popular. The LSMC utilizes linear...

master thesis 2023

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Neural networks-based algorithms for option pricing

Rou, Jasper (author)

In this research, we consider neural network-algorithms for option pricing. We use the Black-Scholes model and the lifted Heston model. We derive the option pricing partial differential equation (PDE), which we solve with a neural network, and the conditional characteristic function of the stock price which leads to the option price with the COS...

master thesis 2022

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Option Pricing Techniques: Using Neural Networks

Van Mieghem, Laurens (author)

With the emergence of more complex option pricing models, the demand for fast and accurate numerical pricing techniques is increasing. Due to a growing amount of accessible computational power, neural networks have become a feasible numerical method for approximating solutions to these pricing models. This work concentrates on analysing various...

master thesis 2022

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European option pricing under the rough Heston model using the COS method

Erkan, K.E. (author)

This thesis is about pricing European options using a Fourier-based numerical method called the COS method under the rough Heston model. Besides examining the efficiency and accuracy of the COS method for pricing options under the rough Heston model, it is also investigated if the rough Heston model produces the advantages of the so-called rough...

master thesis 2020

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The Lamperti Transform: Applications to Stochastic Local Volatility Models

de Boer, S.G. (author)

This thesis showcases a rather contemporary method of solving a generalized system of stochastic differential equations (SDE's) comparable to the SABR model. The solution is derived from a stochastic-local volatility (SLV) model in which the local volatility (LV) component is kept general. This generality is maintained throughout all derivations...

master thesis 2020

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Pricing Options and Computing Implied Volatilities using Neural Networks

Liu, S. (author), Oosterlee, C.W. (author), Bohte, Sander M. (author)

This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options and to calculate implied volatilities with the aim of accelerating the corresponding numerical methods. With ANNs being universal function approximators, this method trains an optimized ANN on a data set generated by a...

journal article 2019

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BENCHOP–SLV: The BENCHmarking project in Option Pricing–Stochastic and Local Volatility problems

von Sydow, Lina (author), Milovanović, Slobodan (author), Larsson, Elisabeth (author), In 't Hout, Karel (author), Wiktorsson, Magnus (author), Oosterlee, C.W. (author), Shcherbakov, Victor (author), Wyns, Maarten (author), Leitao Rodriguez, A. (author), Jain, S. (author), Haentjens, Tinne (author), Waldén, Johan (author)

In the recent project BENCHOP–the BENCHmarking project in Option Pricing we found that Stochastic and Local Volatility problems were particularly challenging. Here we continue the effort by introducing a set of benchmark problems for this type of problems. Eight different methods targeted for the Stochastic Differential Equation (SDE)...

journal article 2018

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Een algoritme voor het prijzen van Amerikaanse opties met behulp van regressie- en variantie reductietechnieken

Roest, Raoul (author)

In tegenstelling tot een Europese optie, is de prijs van een Amerikaanse optie vaak niet te berekenen met behulp van standaard analysemethoden. Om toch een optieprijs te kunnen bepalen, wordt er gebruik gemaakt van simulatiemethoden. In stochastische modellen, gebaseerd op zogenoemde arbitragevrije prijsbepalingen, is de optieprijs gelijk aan de...

bachelor thesis 2017

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Forecasting the implied volatility surface in risk-management applications

van Dijk, Marcel (author)

In risk-management, one typically simulates many states of the market using models that are in line with historical data, also known as real-world models. For example, new regulations require insurance companies to value their position on a 1-year horizon. Insurance companies issue guarantees that need to be valued according to market...

master thesis 2017

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On the Application of Shannon Wavelet Inverse Fourier Techniques: An Extension to Asian Option Valuation and European Option Pricing under the SABR Model

Wagner, Emma (author)

This work is on the extension of the SWIFT method to option pricing problems where the sum of lognormals occurs. The SWIFT method (ShannonWavelet Inverse Fourier Technique) is extended to the valuation of geometric Asian options and arithmetic Asian options with a Lévy process as underlying price process and the valuation of European options...

master thesis 2017

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Valuation and Hedging of Correlation Swaps

Draijer, Mats (author)

The aim of this thesis is to provide a formula for the value of a correlation swap. To get to this formula, a model from an article by Bossu is inspected and its resulting expression for fair the fair value of a correlation swap is simulated. The Jacobi process will be defined and two discretization schemes will be compared for it. Methods are...

bachelor thesis 2017

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Numerical Solutions for the Stochastic Local Volatility Model

van der Weijst, Roel (author)

This thesis is about pricing European options and forward start options under the Heston LSV model. The impact of conditionally calibrating the Heston parameters on the satisfaction of the Feller condition and thereafter correcting with a local volatility surface is investigated here. The results show that this approach is computationally time...

master thesis 2017

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The Heston model with Term Structure: Option Pricing and Calibration

van der Zwaard, T. (author)

This thesis addresses the calibration of the Heston model with term structure (i.e. with piecewise constant parameters) to a set of European option prices from the FX market. Several option pricing methods are discussed and compared, among which the COS method, Lewis' method and the Andersen QE Monte Carlo scheme. Several modifications are...

master thesis 2016

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Radial basis functions for option pricing in insurance liabilities

Schols, E. (author)

This thesis discusses the valuation of embedded options in insurance liabilities using radial basis functions. For insurance companies, the valuation of embedded options is an important topic within risk management. This valuation can become too computationally heavy when nested Monte Carlo simulations are used. To overcome this computational...

master thesis 2016

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A Highly Efficient Shannon Wavelet Inverse Fourier Technique for Pricing European Options

Ortiz-Gracia, Luis (author), Oosterlee, C.W. (author)

In the search for robust, accurate, and highly efficient financial option valuation techniques, we here present the SWIFT method (Shannon wavelets inverse Fourier technique), based on Shannon wavelets. SWIFT comes with control over approximation errors made by means of sharp quantitative error bounds. The nature of the local Shannon wavelets...

journal article 2016

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Reduction of Computing Time for Numerical Pricing of European Multi-dimensional Options based on the COS Method

Hazenoot, D. (author)

Numerical integration methods such as the Fourier-based COS method can be used for effciently and accurately pricing financial products. The COS method can be applied to options on one underlying stock as well as on multiple underlying stocks. However, this method suffers from an exponential increase in computational complexity as the dimensions...

master thesis 2016

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Pricing options on gas under a regime-switching model

Van Tol, L.J.M. (author)

This thesis deals with pricing options on natural gas under a regime-switching model. First of all, a regime-switching model for natural gas is considered. Hereafter, historical gasdata are examined to find a model which fits the data. Next, a system of PDE's is derived in order to price an option under the regime-switching model. Finally,...

bachelor thesis 2015